Ajin George Joseph

Reinforcement Learning · 2019

A researcher in the Science corpus: 1 paper; trusts 20 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 24 citations into it
• Artificial Intelligence — 20 citations into it
• Management Science and Operations Research — 6 citations into it
• Optimization & Training — 5 citations into it

Whom Ajin George Joseph trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Richard S. Sutton
2. Vivek Shripad Borkar
3. Harold J. Kushner
4. Csaba Szepesvari
5. A. Mahmood
6. Huizhen Yu
7. Andrew Barto
8. Hamid Reza Maei
9. Tamer Basar
10. Steven J. Bradtke

Papers from Ajin George Joseph's perspective

Ordered by how strongly the researchers Ajin George Joseph trusts endorse each paper. Same corpus, a different order for every researcher.

1. Reinforcement Learning: An Introduction
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Gradient-based learning applied to document recognition
5. Human-level control through deep reinforcement learning
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Long Short-Term Memory
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Understanding the difficulty of training deep feedforward neural networks
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Two-Timescale Networks for Nonlinear Value Function Approximation (2019) — 51 citations